If you are looking to buy some books in probability here are some of the best books to learn the art of Probability

The Probability Tutoring Book: An Intuitive Course for Engineers and Scientists (and Everyone Else!)

A good book for graduate level classes: has some practice problems in them which is a good thing. But that doesn't make this book any less of buy for the beginner.

An Introduction to Probability Theory and Its Applications, Vol. 1, 3rd Edition

This is a two volume book and the first volume is what will likely interest a beginner because it covers discrete probability. The book tends to treat probability as a theory on its own

Discovering Statistics Using R

This is a good book if you are new to statistics & probability while simultaneously getting started with a programming language. The book supports R and is written in a casual humorous way making it an easy read. Great for beginners. Some of the data on the companion website could be missing.

Fifty Challenging Problems in Probability with Solutions (Dover Books on Mathematics)

This book is a great compilation that covers quite a bit of puzzles. What I like about these puzzles are that they are all tractable and don't require too much advanced mathematics to solve.

Introduction to Probability Theory

Overall an excellent book to learn probability, well recommended for undergrads and graduate students

Probability Theory: A Concise Course (Dover Books on Mathematics)

Dover books are great, they cost less + they tend to have nice pencil-like images which anyone who likes mathematics would love. This book covers a lot in its concise set of pages. Do note, that you need some basic grasp of mathematics/statistics in general to gain from this book. But well worth the buy.

Introduction to Probability, 2nd Edition

A good book to own. Does not require prior knowledge of other areas, but the book is a bit low on worked out examples.

Ramanujan's Lost Notebook

This book covers findings of the genius Ramanujan's lost notebook. Most of his findings were scribbled in notebooks without proof. Mathematicians later recovered this book, provided proofs and mapped his adhoc findings to later discoveries. Own this if you are fascinated by his work.

Bundle of Algorithms in Java, Third Edition, Parts 1-5: Fundamentals, Data Structures, Sorting, Searching, and Graph Algorithms (3rd Edition) (Pts. 1-5)

An excellent resource (students, engineers and even entrepreneurs) if you are looking for some code that you can take and implement directly on the job

Understanding Probability: Chance Rules in Everyday Life

This is a great book to own. The second half of the book may require some knowledge of calculus. It appears to be the right mix for someone who wants to learn but doesn't want to be scared with the "lemmas"

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems)

This one is a must have if you want to learn machine learning. The book is beautifully written and ideal for the engineer/student who doesn't want to get too much into the details of a machine learned approach but wants a working knowledge of it. There are some great examples and test data in the text book too.

A Course in Probability Theory, Third Edition

Covered in this book are the central limit theorem and other graduate topics in probability. You will need to brush up on some mathematics before you dive in but most of that can be done online

Probability and Statistics (4th Edition)This book has been yellow-flagged with some issues: including sequencing of content that could be an issue. But otherwise its good

The Probability Tutoring Book: An Intuitive Course for Engineers and Scientists (and Everyone Else!)

A good book for graduate level classes: has some practice problems in them which is a good thing. But that doesn't make this book any less of buy for the beginner.

An Introduction to Probability Theory and Its Applications, Vol. 1, 3rd Edition

This is a two volume book and the first volume is what will likely interest a beginner because it covers discrete probability. The book tends to treat probability as a theory on its own

Discovering Statistics Using R

This is a good book if you are new to statistics & probability while simultaneously getting started with a programming language. The book supports R and is written in a casual humorous way making it an easy read. Great for beginners. Some of the data on the companion website could be missing.

Fifty Challenging Problems in Probability with Solutions (Dover Books on Mathematics)

This book is a great compilation that covers quite a bit of puzzles. What I like about these puzzles are that they are all tractable and don't require too much advanced mathematics to solve.

Introduction to Probability Theory

Overall an excellent book to learn probability, well recommended for undergrads and graduate students

Probability Theory: A Concise Course (Dover Books on Mathematics)

Dover books are great, they cost less + they tend to have nice pencil-like images which anyone who likes mathematics would love. This book covers a lot in its concise set of pages. Do note, that you need some basic grasp of mathematics/statistics in general to gain from this book. But well worth the buy.

Introduction to Probability, 2nd Edition

A good book to own. Does not require prior knowledge of other areas, but the book is a bit low on worked out examples.

Ramanujan's Lost Notebook

This book covers findings of the genius Ramanujan's lost notebook. Most of his findings were scribbled in notebooks without proof. Mathematicians later recovered this book, provided proofs and mapped his adhoc findings to later discoveries. Own this if you are fascinated by his work.

Bundle of Algorithms in Java, Third Edition, Parts 1-5: Fundamentals, Data Structures, Sorting, Searching, and Graph Algorithms (3rd Edition) (Pts. 1-5)

An excellent resource (students, engineers and even entrepreneurs) if you are looking for some code that you can take and implement directly on the job

Understanding Probability: Chance Rules in Everyday Life

This is a great book to own. The second half of the book may require some knowledge of calculus. It appears to be the right mix for someone who wants to learn but doesn't want to be scared with the "lemmas"

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems)

This one is a must have if you want to learn machine learning. The book is beautifully written and ideal for the engineer/student who doesn't want to get too much into the details of a machine learned approach but wants a working knowledge of it. There are some great examples and test data in the text book too.

A Course in Probability Theory, Third Edition

Covered in this book are the central limit theorem and other graduate topics in probability. You will need to brush up on some mathematics before you dive in but most of that can be done online

Probability and Statistics (4th Edition)This book has been yellow-flagged with some issues: including sequencing of content that could be an issue. But otherwise its good

Another excellent introductory probability book is

ReplyDeleteHenk Tijms, Understanding Probability, 3rd ed., Cambridge University Press, 2012,

see http://personal.vu.nl/h.c.tijms for more info. It is a peerless probability book that contains a wonderful introduction to Bayesian inference amongst others.

Thanks for the quote. It appears to be a good read, though a bit pricy when compared to the fifty challenging problems book. I like it all the same

ReplyDeleteAre there probability textbooks for mathematicians who already know some measure theory, abstract algebra etc.?

ReplyDeleteGood question. In general, I want to recommend only books that are generally readable. A way I flag a book as unreadable for the beginner-statistician/engineer is a book that is filled with lemma's & theorems and offer no "plain-english" explanation of concepts. But if you are really into it, I would recommend getting into text books that deal with quantum physics which requires a fairly daunting amount of probabilistic math or subscribe to http://www.amstat.org/publications/jasa.cfm and read up the papers.

ReplyDeleteHowever, there is one I would definitely recommend, it is on machine learning and gives a good mix of plain-speak and technical math.